BACKGROUND: Machine learning algorithms are essential for predicting severe outcomes during public health crises like COVID-19. However, the dynamic nature of diseases requires continual evaluation and updating of these algorithms. This study aims to...
OBJECTIVES: To construct a diagnostic model for mixed dentition using a multistage deep-learning network to predict potential ectopic eruption in permanent teeth by integrating dentition segmentation into the process of automatic classification of de...
Respiration; international review of thoracic diseases
Oct 17, 2024
INTRODUCTION: Simulation-based training has proven effective for learning flexible bronchoscopy. However, no studies have tested the efficacy of training toward established proficiency criteria, i.e., mastery learning (ML). We wish to test the effect...
American journal of pharmaceutical education
Oct 17, 2024
OBJECTIVE: This study explored student pharmacists' perceptions and attitudes regarding artificial intelligence (AI) and machine learning (ML) in pharmacy practice. Due to AI/ML's promising prospects, understanding students' current awareness, compre...
Epileptic seizure prediction plays a crucial role in enhancing the quality of life for individuals with epilepsy. Over recent years, a multitude of deep learning-based approaches have emerged to tackle this challenging task, leading to significant ad...
OBJECTIVE: Investigation of explainable deep learning methods for graph neural networks to predict HIV infections with social network information and performing domain adaptation to evaluate model transferability across different datasets.
BACKGROUND: Distinguishing between unilateral and bilateral primary aldosteronism, a major cause of secondary hypertension, is crucial due to different treatment approaches. While adrenal venous sampling is the gold standard, its invasiveness, limite...
OBJECTIVE: To perform a comparative analysis of the three-level triage protocol conducted by triage nurses and emergency medicine doctors with the use of ChatGPT, Gemini, and Pi, which are recognized artificial intelligence (AI) models widely used in...
BACKGROUND: Obtaining and describing semiology efficiently and classifying seizure types correctly are crucial for the diagnosis and treatment of epilepsy. Nevertheless, there exists an inadequacy in related informatics resources and decision support...
PURPOSE: Stereopsis, the ability of humans to perceive depth through distinct visual stimuli in each eye, is foundational to autostereoscopic technology in computing. However, ensuring stable head position during assessments has been challenging. Thi...
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